10 hours ago
Hyderābād, IndiaStaff+
Responsibilities
- Architect and build production-ready generative AI and agentic AI applications and workflows.
- Deploy, monitor, and optimize LLM-powered workflows, multi-agent coordination, and orchestration pipelines.
- Integrate AI applications with existing systems and implement prompt engineering, RAG, contextual memory, and MCP patterns.
- Develop AI agents capable of reasoning, planning, and multi-step task execution.
- Build evaluation, testing, logging, monitoring, and observability pipelines for AI systems.
- Optimize AI workflows for latency, cost efficiency, reliability, and scalability.
- Mentor developers and AI engineers and provide technical guidance.
- Own architectural decisions, coding standards, reusable patterns, and engineering best practices.
- Apply AI governance, responsible AI, auditability, transparency, data-handling controls, and risk mitigation practices.
- Research emerging AI tools and frameworks and document reproducible AI engineering processes.
Requirements
- 8+ years of professional software development experience with .NET, React, or full-stack development, including mentorship or team leadership experience.
- At least 2 years of hands-on experience building generative AI or agentic AI applications.
- Strong proficiency in Python and backend engineering principles.
- Experience designing RESTful APIs and scalable service architectures.
- Practical experience with LLM APIs, embeddings, vector search, or RAG pipelines.
- Working knowledge of AI governance, responsible AI practices, or compliance considerations.
- Familiarity with agent frameworks and autonomous decision workflows.
- Understanding of data structures, system design, performance optimization, and analytical problem-solving.
- Preferred: experience deploying AI applications in cloud environments, preferably AWS.
- Preferred: familiarity with vector databases, knowledge retrieval architectures, Git, production deployments, Docker, Kubernetes, AI-agent evaluation or monitoring pipelines, AI safety, guardrails, distributed systems, or event-driven architecture.
Categories
About Verisk
Verisk builds data analytics platforms, predictive models, and software used by property and casualty insurers to underwrite, price, detect fraud, and manage claims. The company monetizes industry-scale datasets, catastrophe risk models, and workflow tools sold by subscription and transaction to insurers, reinsurers, and brokers worldwide. Founded in 1971 and headquartered in Jersey City, New Jersey, Verisk is a public company trading on Nasdaq (VRSK).